Triple
T8220394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Windows Basic |
E192043
|
entity |
| Predicate | 3DEffects |
P16366
|
FINISHED |
| Object | reduced |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: reduced | Statement: [Windows Basic, 3DEffects, reduced]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 3DEffects Context triple: [Windows Basic, 3DEffects, reduced]
-
A.
projectionEffect
Indicates the visual or spatial transformation produced when something is projected from one surface, medium, or viewpoint onto another.
-
B.
visualEffect
chosen
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
C.
rotationEffect
Indicates that one entity is rotated around a specified point or axis by a given angle, affecting its orientation relative to other entities.
-
D.
has3DModels
Indicates that an entity is associated with one or more three-dimensional (3D) digital models representing it.
-
E.
supports3DAcceleration
Indicates that one entity provides or enables hardware- or software-based 3D graphics acceleration for another entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca82c9a8ac81908b011c38698456e4 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb77c782a8819086019ab6bac05749 |
completed | March 31, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69cb36af41e081909dee92b9bc4947f1 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:45 p.m.